客户时序关联规则挖掘方法研究

• 论文 •

客户时序关联规则挖掘方法研究

闫相斌，李一军，张洁

哈尔滨工业大学管理学院，黑龙江哈尔滨 150001

收稿日期:2004-11-10 修回日期:2005-01-31 出版日期:2006-01-15 发布日期:2006-01-25
基金资助:
国家自然科学基金资助项目（70171013）；国家863/CIMS主题资助项目（2001AA136010）。

Research on customer temporal sequence association rule mining method

YAN Xiang-bin, LI Yi-jun, ZHANG Jie

Sch. of Management, Harbin Inst. of Tech., Harbin 150001, China

Received:2004-11-10 Revised:2005-01-31 Online:2006-01-15 Published:2006-01-25
Supported by:
Project support by the National Natural Science Foundation, China(No. 70171013) and the National Hi-Tech. R&D Program for CIMS,China (No. 2001AA136010).

摘要/Abstract

摘要： 针对客户交易数据的特点，提出了一种基于前缀映射累加树的客户时序关联规则发现方法。将时间窗口内频繁项的信息映射到前缀映射累加树中，以降低频繁时序模式的搜索空间，提高时序关联规则的挖掘效率。另外，通过为特定的频繁项建立前缀映射累加树，可以挖掘特定的时序关联规则，并能以较精确的方式，发现具有一定模糊性的客户时序关联规则。实验结果表明，所提出的方法能够提高客户时序关联规则的挖掘效率。

关键词: 客户, 时序关联规则, 前缀映射累加树

Abstract: According to the characteristics of customers transaction database, a novel customer temporal sequence association rules mining method was proposed which was based on prefix projected accumulation tree. The searching space of frequent temporal sequence patterns could be reduced and the efficiency of association rule mining could be improved by projecting frequent items in time windows to prefix projected accumulation trees. Through building of prefix projected accumulation tree for specific frequent items, the proposed method could regard specific rule as a mining goal and find fuzzy rules in precise way. Experimental results indicated that the proposed method has improved the efficiency of customer temporal sequence association rule mining.

Key words: customer, temporal sequence association rule

中图分类号:

TP391

闫相斌，李一军，张洁. 客户时序关联规则挖掘方法研究[J]. .

YAN Xiang-bin, LI Yi-jun, ZHANG Jie. Research on customer temporal sequence association rule mining method[J]. .

参考文献

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